Jongjoo Park

IEC 61850 Standard Based MMS Communication Stack Design Using OOP

This paper deals with the MMS communication stack library based on IEC 61850 standard. IEC 61850 standard is communication protocol of substation automation for converting conventional copper-wired type to Ethernet based open architecture in digital method. With IEC 61850 standard, interoperability can be maximized. With IEC 61850, optimal use and prediction of troubles are done through real-time surveillance by substation system. Starting from European market, substation automation systems (Sass) based on IEC61850 are spreading trend. Trying to stay with the trend, communication stack library is needed. IEC 61850 standard consists of object, we adopt the strategy of using object-oriented programming (OOP) based on C++ language. Therefore we can take advantages of maintenance, management, alteration and reuse. For improving power of OOP method, we adopt design pattern, especially singleton pattern. With these two strategies, this paper layers the library into a dozen or more layer to provide developers ease of use. We simulate this library by making Microsoft Windows programs.

Color filter array interpolation method for Bayer-like W-RGB pattern

In this paper, the color filter array interpolation method for Bayer-like White-pattern is proposed. Conventional methods have defects that blur cannot be removed effectively near edges because of rough averaging. To overcome the defection, proposed algorithm utilizes the all direction of edge information, interpolates all color values according to edge direction. Two simulations were done by using test images which are made by eliminating particular color channels by force and real W-RGB mosaicked image taken by W-RGB sensor.

Contrast enhancement with slope modification

In this paper, we propose Adaptive Histogram Equalization (AHE) based contrast enhancement algorithm. Most histogram-based contrast enhancement methods have problems such as excessive contrast enhancement, unnatural output images, and the loss of visual information. The proposed method manipulates the slope of the input of the Probability Density Function (PDF) histogram. Our method adaptively enhances the contrast of the input image and shows good simulation results compared with conventional methods.

Edge-preserving demosaicing method for digital cameras with Bayer-like W-RGB color filter array

A demosaicing method for a Bayer-like W-RGB color filter array (CFA) is proposed. When reproducing images from a W-RGB CFA, conventional color separation methods for W-RGB CFA are likely to cause blurring near the edges due to rough averaging using a color ratio of neighboring pixels. Moreover, these methods cannot be applied to real-life digital cameras with W-RGB CFA because the methods were proposed under an ideal situation, W=R+G+B, not a real-life situation, W≠R+G+B. To improve edge performance, we propose a method of constant color difference assumption with inversed weight, which uses information from all edge directions for interpolating all missing color channels. The proposed method calculates the correlation between W, R, G, and B to enable its application to real-life digital cameras with W-RGB CFA. Simulations were performed to evaluate the proposed method using images captured from a real-life digital camera with W-RGB CFA. Simulation results shows that we can demosaic by using the proposed algorithm compared with the conventional one in about +34.79% SNR, +11.43% PSNR, +1.54% SSIM and 14.02% S-CIELAB error. Thus, the proposed method demosaics better than the conventional methods.

Blurring image quality assessment method based on histogram of gradient

In this paper we propose a blurring image quality assessment (IQA) based on histogram of oriented gradients (HOG). The image quality can be determined by the slope value of the HOG of the target image. The representative line of HOG is approximated by a random sample consensus set (RANSAC). Simulation results performed on the LIVE image quality assessment database show that the proposed method aligns better with how the human visual system perceives image quality than several state-of-the-art IQAs.

Improved physical-like virtual color filter for color separation of White-RGB CMOS sensor

White-RGB (WRGB) color filter array (CFA)-based CMOS sensor is a new and popular technique to improve the image quality directly with a higher sensitivity White (W) filter. Considering there is no color information in the pixel assigned to W, color separation from W raw data is necessary. We propose a color separation method based on a novel physicallike virtual color filters model for the WRGB CFA-based imaging system. The proposed algorithm can reproduce full color signal from W. In the filtering stage, the proposed algorithm provides three channel filter modes to imitate the physical color filter based on the wavelength responses. To reduce the deviation of the spectrum, a supervised learning technique is utilized to obtain the parameters. The Datacolor SpyderCheckr-based experimental results demonstrate that the proposed algorithm provides high accuracy color without the color artifact caused by the error of virtual filter, and the average improvement compared with the Gaussian ideal filter model is almost 90%.

Adaptive Object-Region-Based Image Pre-Processing for a Noise Removal Algorithm

A pre-processing system for adaptive noise removal is proposed based on the principle of identifying and filtering object regions and background regions. Human perception of images depends on bright, well-focused object regions; these regions can be treated with the best filters, while simpler filters can be applied to other regions to reduce overall computational complexity. In the proposed method, bright region segmentation is performed, followed by segmentation of object and background regions. Noise in dark, background, and object regions is then removed by the median, fast bilateral, and bilateral filters, respectively. Simulations show that the proposed algorithm is much faster than and performs nearly as well as the bilateral filter (which is considered a powerful noise removal algorithm); it reduces computation time by 19.4 % while reducing PSNR by only 1.57 % relative to bilateral filtering. Thus, the proposed algorithm remarkably reduces computation while maintaining accuracy.